As businesses expand and enterprises grow in nature, the data that an organization needs to manage also grows. Whether it is a small start-up company with limited systems and processes, or a large entity spanning multiple geographies across the world, with hundreds of machines networked together, the need to capture data and store it for future use is omnipresent. Adding to the complexity of dealing with a large amount of data is the difficulty of managing different kinds of data in various formats, which may have originated from a variety of data sources. For example, the data from a human resource system might be very different from the data that may originate in a sales system.
A data warehouse is a repository of data designed to support management decision making. A data warehouse has evolved due to complex requirements that data management requires. It supports the process of moving data from different source systems so that the data could be stored in an integrated manner for future reference. A data warehouse typically supports a wide variety of management reports or data mining models highlighting business conditions that may be present at a particular point in time. It's a repository of an organization's stored and historical data which enables the management to take business decisions.
Considering that data in a data warehouse may come from a variety of sources and in different formats, an efficient data loading mechanism is always desirable.